---
title: "NYC Restaurants Inspection Analysis Dashboard"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    source: embed
    theme: sandstone
---

```{r setup, include=FALSE, echo = FALSE}
library(flexdashboard)
library(p8105.datasets)
library(tidyverse)
library(plotly)
library(lubridate)
```

Column {data-width=500}
-----------------------------------------------------------------------

### Chart A

```{r, echo = FALSE, message = FALSE}
rest_inspec %>% 
  janitor::clean_names() %>% 
  mutate(inspection_date <- as.Date(inspection_date)) %>%
  filter(inspection_date >= as.Date("2014-01-01"), 
         score != "Missing", boro != "Missing") %>%
  mutate(year = year(inspection_date)) %>%
   plot_ly(x = ~boro, y = ~score, type = "box",
    color = ~boro, frame = ~year, alpha = 0.5) %>% 
  layout(title = "The Distribution of Restaurant Inspection Scores in NYC Boroughs",
         xaxis = list(title = "Borough"),
         yaxis = list(title = "Score"),
         font = list(size = 9))
```

### Chart B

```{r, echo = FALSE, message = FALSE}
rest_inspec %>% 
  janitor::clean_names() %>% 
  mutate(inspection_date <- as.Date(inspection_date)) %>%
  filter(inspection_date >= as.Date("2014-01-01"), 
         score != "Missing", score >= 0, boro != "Missing") %>%
  mutate(year = year(inspection_date)) %>%
  mutate(grade = case_when(0 <= score & score <= 13 ~ "A",
                         14 <= score & score <= 27 ~ "B",
                         score >= 28 ~ "C")) %>%
  group_by(boro,grade, year) %>%
  summarise(Count = n()) %>%
  rename(Grade = grade) %>%
  plot_ly(x = ~boro, y = ~Count, color = ~Grade, 
          frame = ~year, type = "bar", alpha = 0.7) %>% 
  layout(title = 
           "Number of Restaurants by Inspection Grade Level in NYC Boroughs",
         xaxis = list(title = "Borough"),
         yaxis = list(title = "Count"),
         font = list(size = 9))
  
```

Column  {data-height=500}
-----------------------------------------------------------------------
### Chart C

```{r, echo = FALSE, message = FALSE, warning = FALSE}
rest_inspec %>%
  filter(violation_code %in% c("08A", "04L")) %>%
  mutate(Date = format(inspection_date, "%Y-%m")) %>%
  group_by(Date, violation_code) %>%
  summarise(count = n()) %>%
  ungroup() %>%
  mutate(violation_code = violation_code %>% fct_relevel("08A", "04L")) %>%
  mutate(violation_code = recode(violation_code, "08A" = "Facility not vermin proof", "04L" = "Evidence of mice or live mice")) %>%
  plot_ly(x = ~Date, y = ~count,
          color = ~violation_code, type = "scatter", 
          mode = "lines", alpha = 0.5) %>%
  layout(title =  "Mice Related Violations over Time in NYC Restaurants",
         xaxis = list(title = "Date"),
         yaxis = list(title = "Count"),
         font = list(size = 10)
         )
  
```

### Chart D

```{r, echo = FALSE, message = FALSE}
  rest_inspec %>%
  filter(violation_code %in% c("08A", "04L")) %>%
  group_by(cuisine_description, violation_code) %>%
  summarise(count = n()) %>%
  ungroup() %>%
  filter(count > 700, cuisine_description != "Chicken") %>%
  mutate(violation_code = recode(violation_code,"04L" = "Evidence of mice or live mice", "08A" = "Facility not vermin proof")) %>%
  mutate(cuisine_description = fct_reorder(cuisine_description, count, .desc = FALSE)) %>%
  mutate(cuisine_description = recode(cuisine_description,"Latin (Cuban, Dominican, Puerto Rican, South & Central American)" = "Latin" )) %>% 
 plot_ly(height = 240, 
   y = ~cuisine_description, x = ~count,
          color = ~violation_code, type = "bar", alpha = 0.7, orientation = 'h') %>%
  layout(title = "Top 12 Worst Cuisines with Mice-related Violations in NYC Boroughs",
         xaxis = list(title = "Count"),
         yaxis = list(title = "Cuisine"),
         font = list(size = 9))
  
```